The importance of the Google DeepMind's AlphaGo Zero AI program is not that it plays Go with frightening level of sophistication. Instead, it true importance is in self-sustaining nature of the program that can learn independently of external information inputs, by simply playing against itself. In other words, Google has finally cracked the self-replicating algorithm.

Yes, there is a 'new thinking' dimension to this as well. Again, quoting from The Atlantic: "A Go enthusiast named Jonathan Hop ...calls the AlphaGo-versus-AlphaGo face-offs “Go from an alternate dimension.” From all accounts, one gets the sense that an alien civilization has dropped a cryptic guidebook in our midst: a manual that’s brilliant—or at least, the parts of it we can understand."

But the real power of AlphaGo Zero version is its autonomous nature.

From the socio-economic perspective, this implies machines that can directly learn complex (extremely complex), non-linear and creative (with shifts of nodes) tasks. This, in turn, opens the AI to the prospect of writing own code, as well as executing tasks that to-date have been thought of as impossible for machines (e.g. combining referential thinking with creative thinking). The idea that coding skills of humans can ever keep up with this progression has now been debunked. Your coding and software engineering degree is not yet obsolete, but your kid's one will be obsolete, and very soon.

Disclaimer

This blog represents my personal views and is not reflective of the views or opinions held by any company, contractor, client or employer I work for currently or have worked for in the past. These views are not an endorsement to take any action in the markets or of any political position, figures or parties.

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